{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Custom URL prefix with Seldon and Ambassador\n",
    "\n",
    "This notebook shows how you can deploy Seldon Deployments with custom Ambassador configuration."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prerequisites\n",
    "\n",
    "You will need\n",
    "\n",
    " - [Git clone of Seldon Core](https://github.com/SeldonIO/seldon-core) running this notebook\n",
    " - A running Kubernetes cluster with kubectl authenticated\n",
    " - [Helm client](https://helm.sh/)\n",
    " - Seldon Core Python Module : `pip install seldon-core`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a Kubernetes Cluster\n",
    "\n",
    "Follow the [Kubernetes documentation to create a cluster](https://kubernetes.io/docs/setup/).\n",
    "\n",
    "Once created ensure ```kubectl``` is authenticated against the running cluster."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "namespace/seldon created\r\n"
     ]
    }
   ],
   "source": [
    "!kubectl create namespace seldon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Context \"minikube\" modified.\r\n"
     ]
    }
   ],
   "source": [
    "!kubectl config set-context $(kubectl config current-context) --namespace=seldon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "clusterrolebinding.rbac.authorization.k8s.io/kube-system-cluster-admin created\r\n"
     ]
    }
   ],
   "source": [
    "!kubectl create clusterrolebinding kube-system-cluster-admin --clusterrole=cluster-admin --serviceaccount=kube-system:default"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install Helm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "serviceaccount/tiller created\n",
      "clusterrolebinding.rbac.authorization.k8s.io/tiller created\n",
      "$HELM_HOME has been configured at /home/clive/.helm.\n",
      "\n",
      "Tiller (the Helm server-side component) has been installed into your Kubernetes Cluster.\n",
      "\n",
      "Please note: by default, Tiller is deployed with an insecure 'allow unauthenticated users' policy.\n",
      "To prevent this, run `helm init` with the --tiller-tls-verify flag.\n",
      "For more information on securing your installation see: https://docs.helm.sh/using_helm/#securing-your-helm-installation\n",
      "Happy Helming!\n"
     ]
    }
   ],
   "source": [
    "!kubectl -n kube-system create sa tiller\n",
    "!kubectl create clusterrolebinding tiller --clusterrole cluster-admin --serviceaccount=kube-system:tiller\n",
    "!helm init --service-account tiller"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waiting for deployment \"tiller-deploy\" rollout to finish: 0 of 1 updated replicas are available...\n",
      "deployment \"tiller-deploy\" successfully rolled out\n"
     ]
    }
   ],
   "source": [
    "!kubectl rollout status deploy/tiller-deploy -n kube-system"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Start seldon-core"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME:   seldon-core\n",
      "LAST DEPLOYED: Tue Apr 16 09:16:25 2019\n",
      "NAMESPACE: seldon-system\n",
      "STATUS: DEPLOYED\n",
      "\n",
      "RESOURCES:\n",
      "==> v1/Secret\n",
      "NAME                                   TYPE    DATA  AGE\n",
      "seldon-operator-webhook-server-secret  Opaque  0     0s\n",
      "\n",
      "==> v1/ClusterRole\n",
      "NAME                          AGE\n",
      "seldon-operator-manager-role  0s\n",
      "\n",
      "==> v1/ClusterRoleBinding\n",
      "NAME                                 AGE\n",
      "seldon-operator-manager-rolebinding  0s\n",
      "\n",
      "==> v1beta1/Deployment\n",
      "NAME                        DESIRED  CURRENT  UP-TO-DATE  AVAILABLE  AGE\n",
      "seldon-spartakus-volunteer  1        0        0           0          0s\n",
      "\n",
      "==> v1/ServiceAccount\n",
      "NAME                        SECRETS  AGE\n",
      "seldon-spartakus-volunteer  1        0s\n",
      "\n",
      "==> v1beta1/ClusterRoleBinding\n",
      "NAME                        AGE\n",
      "seldon-spartakus-volunteer  0s\n",
      "\n",
      "==> v1/Pod(related)\n",
      "NAME                                  READY  STATUS             RESTARTS  AGE\n",
      "seldon-operator-controller-manager-0  0/1    ContainerCreating  0         0s\n",
      "\n",
      "==> v1/ConfigMap\n",
      "NAME                     DATA  AGE\n",
      "seldon-spartakus-config  3     0s\n",
      "\n",
      "==> v1beta1/CustomResourceDefinition\n",
      "NAME                                         AGE\n",
      "seldondeployments.machinelearning.seldon.io  0s\n",
      "\n",
      "==> v1/Service\n",
      "NAME                                        TYPE       CLUSTER-IP   EXTERNAL-IP  PORT(S)  AGE\n",
      "seldon-operator-controller-manager-service  ClusterIP  10.106.7.42  <none>       443/TCP  0s\n",
      "\n",
      "==> v1/StatefulSet\n",
      "NAME                                DESIRED  CURRENT  AGE\n",
      "seldon-operator-controller-manager  1        1        0s\n",
      "\n",
      "==> v1beta1/ClusterRole\n",
      "NAME                        AGE\n",
      "seldon-spartakus-volunteer  0s\n",
      "\n",
      "\n",
      "NOTES:\n",
      "NOTES: TODO\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!helm install ../../../helm-charts/seldon-core-operator --name seldon-core --set usageMetrics.enabled=true   --namespace seldon-system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "partitioned roll out complete: 1 new pods have been updated...\r\n"
     ]
    }
   ],
   "source": [
    "!kubectl rollout status deploy/seldon-controller-manager -n seldon-system"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup Ingress\n",
    "Please note: There are reported gRPC issues with ambassador (see https://github.com/SeldonIO/seldon-core/issues/473)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME:   ambassador\n",
      "LAST DEPLOYED: Tue Apr 16 09:16:36 2019\n",
      "NAMESPACE: seldon\n",
      "STATUS: DEPLOYED\n",
      "\n",
      "RESOURCES:\n",
      "==> v1/ServiceAccount\n",
      "NAME        SECRETS  AGE\n",
      "ambassador  1        0s\n",
      "\n",
      "==> v1beta1/ClusterRole\n",
      "NAME        AGE\n",
      "ambassador  0s\n",
      "\n",
      "==> v1beta1/ClusterRoleBinding\n",
      "NAME        AGE\n",
      "ambassador  0s\n",
      "\n",
      "==> v1/Service\n",
      "NAME               TYPE          CLUSTER-IP     EXTERNAL-IP  PORT(S)                     AGE\n",
      "ambassador-admins  ClusterIP     10.110.148.36  <none>       8877/TCP                    0s\n",
      "ambassador         LoadBalancer  10.102.23.33   <pending>    80:32682/TCP,443:30170/TCP  0s\n",
      "\n",
      "==> v1/Deployment\n",
      "NAME        DESIRED  CURRENT  UP-TO-DATE  AVAILABLE  AGE\n",
      "ambassador  3        3        3           0          0s\n",
      "\n",
      "==> v1/Pod(related)\n",
      "NAME                         READY  STATUS             RESTARTS  AGE\n",
      "ambassador-5b89d44544-6g9fv  0/1    ContainerCreating  0         0s\n",
      "ambassador-5b89d44544-8n7rp  0/1    ContainerCreating  0         0s\n",
      "ambassador-5b89d44544-dwcxd  0/1    ContainerCreating  0         0s\n",
      "\n",
      "\n",
      "NOTES:\n",
      "Congratuations! You've successfully installed Ambassador.\n",
      "\n",
      "For help, visit our Slack at https://d6e.co/slack or view the documentation online at https://www.getambassador.io.\n",
      "\n",
      "To get the IP address of Ambassador, run the following commands:\n",
      "NOTE: It may take a few minutes for the LoadBalancer IP to be available.\n",
      "     You can watch the status of by running 'kubectl get svc -w  --namespace seldon ambassador'\n",
      "\n",
      "  On GKE/Azure:\n",
      "  export SERVICE_IP=$(kubectl get svc --namespace seldon ambassador -o jsonpath='{.status.loadBalancer.ingress[0].ip}')\n",
      "\n",
      "  On AWS:\n",
      "  export SERVICE_IP=$(kubectl get svc --namespace seldon ambassador -o jsonpath='{.status.loadBalancer.ingress[0].hostname}')\n",
      "\n",
      "  echo http://$SERVICE_IP:\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!helm install stable/ambassador --name ambassador --set crds.keep=false"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waiting for deployment \"ambassador\" rollout to finish: 0 of 3 updated replicas are available...\n",
      "Waiting for deployment \"ambassador\" rollout to finish: 1 of 3 updated replicas are available...\n",
      "Waiting for deployment \"ambassador\" rollout to finish: 2 of 3 updated replicas are available...\n",
      "deployment \"ambassador\" successfully rolled out\n"
     ]
    }
   ],
   "source": [
    "!kubectl rollout status deployment.apps/ambassador"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Port Forward to Ambassador\n",
    "\n",
    "```\n",
    "kubectl port-forward $(kubectl get pods -n seldon -l app.kubernetes.io/name=ambassador -o jsonpath='{.items[0].metadata.name}') -n seldon 8003:8080\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Launch main model\n",
    "\n",
    "We will create a very simple Seldon Deployment with a dummy model image `seldonio/mock_classifier:1.0`. This deployment is named `example`. We will add custom Ambassador config which sets the Ambassador prefix to `/mycompany/ml`\n",
    "\n",
    "We must ensure we set the correct service endpoint. Seldon Core creates an endpoint of the form:\n",
    " \n",
    "`<spec.name>-<metadata.name>.<namespace>:<port>`\n",
    "\n",
    "Where\n",
    "\n",
    "  * `<spec-name>` is the name you give to the Seldon Deployment spec: `production-model` below\n",
    "  * `<metadata.name>` is the metadata name in the Seldon Deployment: `example` below\n",
    "  * `<namespace>` is the namespace your Seldon Deployment is deployed to\n",
    "  * `<port>` is the port either 8000 for REST or 5000 for gRPC\n",
    "  \n",
    "This will allow you to set the `service` value in the Ambassador config you create. So for the example below we have:\n",
    "\n",
    "```\n",
    "service: production-model-example.seldon:8000\n",
    "```\n",
    "  \n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\r\n",
      "    \u001b[34;01m\"apiVersion\"\u001b[39;49;00m: \u001b[33m\"machinelearning.seldon.io/v1alpha2\"\u001b[39;49;00m,\r\n",
      "    \u001b[34;01m\"kind\"\u001b[39;49;00m: \u001b[33m\"SeldonDeployment\"\u001b[39;49;00m,\r\n",
      "    \u001b[34;01m\"metadata\"\u001b[39;49;00m: {\r\n",
      "        \u001b[34;01m\"labels\"\u001b[39;49;00m: {\r\n",
      "            \u001b[34;01m\"app\"\u001b[39;49;00m: \u001b[33m\"seldon\"\u001b[39;49;00m\r\n",
      "        },\r\n",
      "        \u001b[34;01m\"name\"\u001b[39;49;00m: \u001b[33m\"example\"\u001b[39;49;00m\r\n",
      "    },\r\n",
      "    \u001b[34;01m\"spec\"\u001b[39;49;00m: {\t\r\n",
      "        \u001b[34;01m\"name\"\u001b[39;49;00m: \u001b[33m\"production-model\"\u001b[39;49;00m,\r\n",
      "\t\u001b[34;01m\"annotations\"\u001b[39;49;00m: {\r\n",
      "\t    \u001b[34;01m\"seldon.io/ambassador-config\"\u001b[39;49;00m:\u001b[33m\"apiVersion: ambassador/v0\\nkind: Mapping\\nname: seldon_example_rest_mapping\\nprefix: /mycompany/ml/\\nservice: production-model-example.seldon:8000\\ntimeout_ms: 3000\"\u001b[39;49;00m\r\n",
      "\t},\t\r\n",
      "        \u001b[34;01m\"predictors\"\u001b[39;49;00m: [\r\n",
      "            {\r\n",
      "                \u001b[34;01m\"componentSpecs\"\u001b[39;49;00m: [{\r\n",
      "                    \u001b[34;01m\"spec\"\u001b[39;49;00m: {\r\n",
      "                        \u001b[34;01m\"containers\"\u001b[39;49;00m: [\r\n",
      "                            {\r\n",
      "                                \u001b[34;01m\"image\"\u001b[39;49;00m: \u001b[33m\"seldonio/mock_classifier:1.0\"\u001b[39;49;00m,\r\n",
      "                                \u001b[34;01m\"imagePullPolicy\"\u001b[39;49;00m: \u001b[33m\"IfNotPresent\"\u001b[39;49;00m,\r\n",
      "                                \u001b[34;01m\"name\"\u001b[39;49;00m: \u001b[33m\"classifier\"\u001b[39;49;00m\r\n",
      "                            }\r\n",
      "                        ],\r\n",
      "                        \u001b[34;01m\"terminationGracePeriodSeconds\"\u001b[39;49;00m: \u001b[34m1\u001b[39;49;00m\r\n",
      "                    }}\r\n",
      "                                  ],\r\n",
      "                \u001b[34;01m\"graph\"\u001b[39;49;00m:\r\n",
      "                {\r\n",
      "                    \u001b[34;01m\"children\"\u001b[39;49;00m: [],\r\n",
      "                    \u001b[34;01m\"name\"\u001b[39;49;00m: \u001b[33m\"classifier\"\u001b[39;49;00m,\r\n",
      "                    \u001b[34;01m\"type\"\u001b[39;49;00m: \u001b[33m\"MODEL\"\u001b[39;49;00m,\r\n",
      "                    \u001b[34;01m\"endpoint\"\u001b[39;49;00m: {\r\n",
      "                        \u001b[34;01m\"type\"\u001b[39;49;00m: \u001b[33m\"REST\"\u001b[39;49;00m\r\n",
      "                    }},\r\n",
      "                \u001b[34;01m\"name\"\u001b[39;49;00m: \u001b[33m\"single\"\u001b[39;49;00m,\r\n",
      "                \u001b[34;01m\"replicas\"\u001b[39;49;00m: \u001b[34m1\u001b[39;49;00m\r\n",
      "            }\r\n",
      "        ]\r\n",
      "    }\r\n",
      "}\r\n"
     ]
    }
   ],
   "source": [
    "!pygmentize model_custom_ambassador.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "seldondeployment.machinelearning.seldon.io/example created\r\n"
     ]
    }
   ],
   "source": [
    "!kubectl create -f model_custom_ambassador.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waiting for deployment \"production-model-single-7cd068f\" rollout to finish: 0 of 1 updated replicas are available...\n",
      "deployment \"production-model-single-7cd068f\" successfully rolled out\n"
     ]
    }
   ],
   "source": [
    "!kubectl rollout status deploy/production-model-single-7cd068f"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from seldon_core.seldon_client import SeldonClient\n",
    "sc = SeldonClient(deployment_name=\"example\",namespace=\"seldon\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### REST Request"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Success:True message:\n",
      "Request:\n",
      "data {\n",
      "  tensor {\n",
      "    shape: 1\n",
      "    shape: 1\n",
      "    values: 0.1628281752658065\n",
      "  }\n",
      "}\n",
      "\n",
      "Response:\n",
      "meta {\n",
      "  puid: \"5lb8edtgn4rhbd03g94g318io7\"\n",
      "  requestPath {\n",
      "    key: \"classifier\"\n",
      "    value: \"seldonio/mock_classifier:1.0\"\n",
      "  }\n",
      "}\n",
      "data {\n",
      "  names: \"proba\"\n",
      "  tensor {\n",
      "    shape: 1\n",
      "    shape: 1\n",
      "    values: 0.059870232304306846\n",
      "  }\n",
      "}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "r = sc.predict(gateway=\"ambassador\",transport=\"rest\",ambassador_prefix=\"/mycompany/ml\")\n",
    "print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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